How are prices set? Pricing your property is an art in itself. It’s a complicated business, demanding a superior understanding of your objectives, each property’s attributes, and most of all, of your market: supply, guests, distribution channels, seasonality, events and ideally, realtime rates, occupancy and demand.
So what are the different approaches that property managers take when pricing their properties? How do they deal with the different demand characteristics of weekends and low seasons for example? We’ve analyzed a data sample of pricing calendars from Hawaii to better understand the different pricing approaches in short term rentals.
The market in Hawaii has two peak seasons, one stretching from December until the end of February, and the other starting around June and peaking in July. The first peak season however – during winter – is the busiest time of the year. Given the market type and geographical situation, guests tend to visit Hawaii for more than just the weekend, indeed, the median length of stay is 7 days. Having these two pieces of information, we set out to look at pricing calendars to form certain ‘pricing profiles’ considering: how often the price is changed, how specific or general the changes are, how far rate changes are made, and whether changes are manual, semi-automated, or automated.
The first segment we found implemented no rate variation – one price is set for the whole year irrespective of market fluctuations – see below. Managers adopting this method may save themselves the hassle of setting different prices, but naturally also miss out on the benefits of higher occupancy or return. We found this approach to be fairly rare.
Single Rate Variation
This rate management profile is more aware of the benefits of adding some variation to their prices, but does so in a rigid and structured manner. They think of one further dimension to their demand and pricing. In the first chart, we see an example of an owner who decides to set a higher price for weekends, but to keep the range fixed throughout the year.
We did also see instances of managers opting to set a lower price during weekends and a higher one on weekdays during the first two weeks of October. We can speculate that the owner wants to encourage longer stays (one-week long possibly) in order to align consecutive reservations and increase his occupancy, while benefiting from a higher price if guests do end up coming in the middle of the week.
The second single variation graph demonstrates a strategy that accounts for the peak season from December to April; setting a higher – but fixed – price for this period. This pricing strategy is very commonly seen.
Our third and final chart for single variation strategies shows a manager who cares about a much more specific time period; they decide to target the heightened demand of Christmas and New Year with a marked up rate.
Basic Rate Variation
Here we have the most common profile of pricing strategy: those managers who modify their price several times a year. While their price variations are neither too intricate nor frequent, these owners implement multiple price points that follow a less rigid pattern of application.
Elaborate Rate Variation
Where we start seeing city skylines in the trace, describing more intricate rate profiles, we are considering more professionalised management. Here, it is likely that property managers are combining their knowledge of the market with their ADR or occupancy objectives in order to set varied rates across different time frames. For example, we can see big drops in price on certain days, and we can speculate that PMs are trying to encourage bookings on these particular days.
Automated Rate Variation
In this final segment we find the managers who utilize pricing software to automate their price variation on a daily basis. The advantage of automating the process is a system allocating an optimal rate based on your parameters and the market demand, rather than manually considering and implementing your price on a regular basis.
However, using dynamic pricing software does not mean that no manual intervention is required. In this particular example, we can see that the price is fixed during certain periods, which suggests that the manager opted to step in and fix the rate during that time. As pricing algorithms work from user-input parameters, it is still important for managers to have a sense of market rates and demand to shape the dynamic implementation.
What all this means
Of course throughout our sample there was a certain degree of arbitrariness. However, as with the examples we presented here, we have identified some clear trends that give us some insight into how managers are approaching their pricing strategy. Different strategies are evident surrounding seasonality, day of week, degree of variation, imposed targets and implementation, and considering the market representation of these different approaches is also interesting. Of our sample, 10% showed no variation in pricing; comparable to those demonstrating automated profiles at 12%. A dominating 57% of listings showed only single or basic rate variation, while elaborate variation was represented by 21% of the market sample. At a combined 33% for elaborate and automated, we can say that roughly a third of this market is professionalised or at least giving their revenue management significant consideration.
We have seen attention in the pricing and revenue management space rising steadily, particularly this year, as the market professionalizes and competition in our industry grows. Indeed, 41% of professional short-term rental property managers who responded to our 2019 US vacation rental survey altered their rates at least weekly, and this is on the rise. This interest has prompted us to launch an online course in vacation rental revenue management – if you would like to learn more about this or our 2019 US VR survey, please reach out to us at email@example.com
Further, if you have an interest in market intelligence and data, we’d like to invite you to book a demo of our incredible dashboard, that gives useful insights on current supply, rates and demand.